Linear Mode Research Articles

Fusion Modes and Number of Fused Rings: Their Impact on Acceptor-Donor-Acceptor Nonfullerene Acceptors in Organic Solar Cells.

The power conversion efficiency (PCE) of organic solar cells (OSCs) devices has surpassed 19% owing to the blooming of fused-ring nonfullerene acceptors (NFAs), especially for acceptor-donor-acceptor (A-D-A) type NFAs. However, the structural effect of the angular/linear fusion mode and number of fused rings for A-D-A type NFAs on the photovoltaic performance in OSCs devices remains unclear. Herein, the A-D-A type NFAs (F-0Cl, IDIC8-H, and ITIC) have been selected to obtain the intrinsic role of structural design strategies including the angular/linear fusion mode and the number of fused rings. The results indicate that compared to the linear fusion mode in ITIC, the angular fusion mode in F-0Cl effectively diminishes electronic vibrational coupling within the low-frequency range, leading to lower charge reorganization during the exciton diffusion process. Meanwhile, it facilitates the generation of multiple charge transfer mechanisms at the donor/acceptor (D/A) interface and increases the rates of hole transfer. On the other hand, the decreased number of fused rings of NFAs could inhibit the exciton decay and charge recombination but increase the rates of exciton diffusion and exciton dissociation for individual NFAs and the rates of electron separation for D/A interface. This work provides theoretical insights into structural design strategies, such as linear/angular fusion, and the number of fused rings of NFA, which presents a promising outlook for further enhancing PCE of high-performance A-D-A type NFAs.

Construction of 1D Molecular Conductive Wires Through a Polarized Gene Weaving Strategy for Efficient Electromagnetic Wave Absorption.

The growing threat of electromagnetic pollution has become a pressing safety concern. Metal-organic framework (MOF) derivatives are considered ideal candidates for mitigating electromagnetic radiation. However, due to the limitations imposed by complex post-processing and disruption of pristine crystal structures, the mechanisms of electromagnetic wave absorption remain unclear, let alone achieving atomic-level regulation in MOF derivatives. Moreover, research on MOF-based electromagnetic wave absorbers (EMWA) has predominantly focused on 2D and 3D structures, leaving 1D MOFs largely unexplored. To address these challenges, a bottom-up polarization gene weaving strategy is proposed to integrate polarizable conjugated groups, thieno(3,2-b)thiophene (TBTT), into two types of conductive MOFs by fine-tuning self-assembly conditions. As expected, both MOFs exhibited strong natural polarization effects. Among them, the 1D linear coordination mode of CuTBTT-1D demonstrated enhanced charge carrier mobility and geometric effects compared to the 2D structure, CuTBTT-2D. The synthesized 1D molecular polarization wire, with a thickness of 2.2mm, achieved ultra-high reflection loss (-77dB) and super-wide absorption bandwidth (6.52GHz). Its performance surpasses that of all known MOF-based EMWAs. This study provides a valuable strategy for the rational design of next-generation 1D MOF EMWA with atomic precision.

Micro-Transfer printing of InGaAs/InP Avalanche Photodiode on Si Substrate

Abstract We report on the fabrication and micro-transfer printing of InGaAs/InP avalanche photodiodes (APDs) onto silicon substrates. A process flow was developed to suspend the devices using semiconductor tethers. The developed process reduces the number of fabrication steps required compared to methods based on the use of photoresist tethers. Furthermore, our process is compatible with devices that may be susceptible to damage induced by the photoresist removal process. APDs were characterised in linear mode operation both before suspension and after printing. Despite the additional fabrication steps required to suspend the APD membranes and the physical nature of the micro-transfer printing process, the electrical characteristics of the devices were preserved. No degradation in the optical performance of the devices was measured. Our work represents the first demonstration of micro-transfer printing of InGaAs/InP avalanche photodiodes onto silicon substrates. The results highlight the viability of micro-transfer printing for effective heterogeneous integration of InGaAs/InP avalanche photodiodes with silicon photonic integrated circuits for optical and quantum communication and other light detection applications.

Internal Transport Barrier triggered by phase synchronizationof Zonal Flow with energetic particle modes

Abstract The suppression of the microturbulence associated
to the emergence of a spontaneous internal transport barrier has been
recently demonstrated in a system showing a possible amplification
of the zonal flow component in the low-frequency regime $\left[\right.$A.
Ghizzo and D. Del Sarto D 2023 \textit{Nucl. Fusion}
\textbf{63} 104002$\left.\right]$.
We use here numerical experiments performed with a ``particle mode''
model based on a double average over the fast cyclotron phase
and over the bounce (or transit) phase to show the major role played
by energetic particles and shear flows in this scenario. \textquotedbl Particle
modes\textquotedbl{} are meant here as classes of particles, identified
by some adiabatic invariant after a gyro-average procedure, which
are associated to the description of some specific linear modes of
the plasma. The introduction of energetic circulating ions or shear
flows into the system makes a larger number of particle modes being
involved in the synchronization process. A global synchronization
of the Fourier modes of the turbulent spectrum can be this way achieved.
This process allows for a bifurcation towards self-organization, which
is associated to the emergence of a staircase-like structure. This
is known to be an essential element in the modification of the zonal
flow pattern in phase space during the suppression of microturbulence
in tokamaks.

High-dimensional anticounterfeiting nanodiamonds authenticated with deep metric learning

Physical unclonable function labels have emerged as a promising candidate for achieving unbreakable anticounterfeiting. Despite their significant progress, two challenges for developing practical physical unclonable function systems remain, namely 1) fairly few high-dimensional encoded labels with excellent material properties, and 2) existing authentication methods with poor noise tolerance or inapplicability to unseen labels. Herein, we employ the linear polarization modulation of randomly distributed fluorescent nanodiamonds to demonstrate, for the first time, three-dimensional encoding for diamond-based labels. Briefly, our three-dimensional encoding scheme provides digitized images with an encoding capacity of 109771 and high distinguishability under a short readout time of 7.5 s. The high photostability and inertness of fluorescent nanodiamonds endow our labels with high reproducibility and long-term stability. To address the second challenge, we employ a deep metric learning algorithm to develop an authentication methodology that computes the similarity of deep features of digitized images, exhibiting a better noise tolerance than the classical point-by-point comparison method. Meanwhile, it overcomes the key limitation of existing artificial intelligence-driven classification-based methods, i.e., inapplicability to unseen labels. Considering the high performance of both fluorescent nanodiamonds labels and deep metric learning authentication, our work provides the basis for developing practical physical unclonable function anticounterfeiting systems.

Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model

In this study, we propose a novel method for retrieving the three-dimensional (3D) wave surface from sea clutter using both simulated and measured data. First, the linear wave superposition model and modulation principle are employed to generate simulated datasets comprising 3D wave surfaces and corresponding sea clutter. Subsequently, we develop a Pix2Pix model enhanced with a self-attention mechanism and a multiscale discriminator to effectively capture the nonlinear relationship between the simulated 3D wave surfaces and sea clutter. The model’s performance is evaluated through error analysis, comparisons of wave number spectra, and differences in wave surface reconstructions using a dedicated test set. Finally, the trained model is applied to reconstruct wave surfaces from sea clutter data collected aboard a ship, with results benchmarked against those derived from the Schrödinger equation. The findings demonstrate that the proposed model excels in preserving high-frequency image details while ensuring precise alignment between reconstructed images. Furthermore, it achieves superior retrieval accuracy compared to traditional approaches, highlighting its potential for advancing wave surface retrieval techniques.

GPLM: Enhancing underwater images with Global Pyramid Linear Modulation

Underwater imagery often suffers from challenges such as color distortion, low contrast, blurring, and noise due to the absorption and scattering of light in water. These degradations complicate visual interpretation and hinder subsequent image processing. Existing methods struggle to effectively address the complex, spatially varying degradations without prior environmental knowledge or may produce unnatural enhancements.To overcome these limitations, we propose a novel method called Global Pyramid Linear Modulation that integrates physical degradation modeling with deep learning for underwater image enhancement. Our approach extends Feature-wise Linear Modulation to a four-dimensional structure, enabling fine-grained, spatially adaptive modulation of feature maps. Our method captures multi-scale contextual information by incorporating a feature pyramid architecture with self-attention and feature fusion mechanisms, effectively modeling complex degradations. We validate our method by integrating it into the MixDehazeNet model and conducting experiments on benchmark datasets. Our approach significantly improves the Peak Signal-to-Noise Ratio, increasing from 28.6 dB to 30.6 dB on the EUVP-515-test dataset. Compared to recent state-of-the-art methods, our method consistently outperforms them by over 3 dB in PSNR on datasets with ground truth. It improves the Underwater Image Quality Measure by more than one on datasets without ground truth. Furthermore, we demonstrate the practical applicability of our method on a real-world underwater dataset, achieving substantial improvements in image quality metrics and visually compelling results. These experiments confirm that our method effectively addresses the limitations of existing techniques by adaptively modeling complex underwater degradations, highlighting its potential for underwater image enhancement tasks.

Conditional Sixth-Harmonic Injection to Improve the Linear Modulation Range of Three-Phase Voltage-Source Converters

Conditional Sixth-Harmonic Injection to Improve the Linear Modulation Range of Three-Phase Voltage-Source Converters

Ultrasonographic Mapping of the Location and Depth of Labial Arteries Prior to Lip Augmentation: A Pilot Study

Aims: This study aims to map the superior and inferior labial arteries in terms of their anatomical location and depth using ultrasound imaging to optimise the planning of lip augmentation procedures in a Brazilian cohort. Study Design: Observational cross-sectional pilot study. Place and Duration of Study: The examinations were conducted at the dental clinic of the University of Fortaleza during October-November 2023. Methodology: Nineteen volunteers (both sexes, aged 18 to 55 years) with no history of previous lip augmentation participated in this study. Imaging was performed using a high-frequency ultrasound machine (Evus 5, Alliage S/A), equipped with a 7–14 MHz linear transducer, in both B-mode and Doppler modes. Statistical analyses included the Shapiro-Wilk test, Levene's test, analysis of variance (ANOVA), T-test, Pearson's correlation coefficient, standard deviation, confidence intervals, and Fisher's exact test, all conducted using Python software. Results: The superior labial artery was predominantly located in the intramuscular region in 68.42% of cases, followed by the submucosa in 31.58%, with no instances in the subcutaneous layer. For the inferior labial artery, a similar distribution was observed: 63.16% intramuscular, 31.58% submucosal, and 5.26% subcutaneous. Statistically significant differences (p < 0.05) were identified in the depth and location of the labial arteries based on sex and specific anatomical regions. Conclusion: This study demonstrates the variation in the depth and location of labial arteries, with a significant predominance in the intramuscular layer. Ultrasound serves as an essential tool for mapping vascular anatomy in the planning of lip augmentation, underscoring the value of thorough anatomical assessment to enhance procedural safety and efficacy.

Sensemaking in organizational storytelling: From linear storytelling to antenarrative

Storytelling can be considered good professional practice for organizational communication as it resonates with stakeholder audiences and contributes to the process of sensemaking. This paper challenges two key assumptions that underpin storytelling in an organizational context. The first assumption is that clarity is the goal of storytelling and therefore linear modes of organizational storytelling should be used to reduce complexity to achieve clarity of understanding of organizational messages. The second assumption is that organizational storytelling consists only of the stories an organization tells about itself, and multiple understandings or ‘mixed messages’ are ‘noise’. This paper will argue that the storytelling concept antenarrative – or narrative fragments that can form emergent storytelling episodes – will expand the parameters of sensemaking in organizational storytelling. Furthermore, listening to emergent storytelling episodes can provide insights into prospective sensemaking, which has implications for organizational storytelling practices in our digital age. Putting antenarrative alongside concepts such as ‘listening’ and ‘engagement’ helps to improve organizational storytelling to work toward more effective organizational communication practice and respond to the challenges of complexity in storytelling, entanglements of the porous organization, and digital disruption.

Numerical study of turbulent eddy self-interaction in tokamaks with low magnetic shear. Part I: Linear simulations

Abstract This study examines the impact of low and zero magnetic shear, along with rational values of safety factor, on linear mode behavior in tokamak plasmas. We focus on how magnetic field line topology and parallel domain length influence linear mode structures and growth rates as magnetic shear decreases. Our results
show that as magnetic shear is reduced to low values, linear modes can transition between different branches, significantly affecting their characteristics. At zero magnetic shear, accurate modeling requires precisely capturing magnetic topology, as small deviations near rational surfaces can greatly impact growth rates. These findings are extended to nonlinear simulations in a companion paper (Volčokas, 2024), revealing that long turbulent eddies and magnetic field line topology play a crucial role in turbulence self-interaction and plasma transport.

Ge-on-Si single-photon avalanche diode using a double mesa structure.

We present experimental results of Ge-on-Si single-photon avalanche diodes based on a novel, to our knowledge, double mesa structure. Using this structure, the electric field at the mesa edges is suppressed compared to a traditional single mesa, leading to significant performance improvements. The dark current in linear mode shows a smaller increase for larger reverse voltages, resulting in a reduction by more than 260 times at low temperatures. Operated in the Geiger-mode at 110 K, the dark count rate in the double mesa is 100 times smaller. The devices achieve a dark count rate of 953 kHz, a single-photon detection efficiency of 7.3%, and a record-low jitter of 81 ps at an excess bias of 17.6% and a temperature of 110 K.

A 2DEG‐Based GaN‐on‐Si Terahertz Modulator with Multi‐Mode Switchable Control

AbstractAs terahertz (THz) technology has been widely considered as a key candidate for future sixth‐generation wireless communication networks, THz modulators show profound significance in wireless communication, data storage, and imaging. In special, dynamic tuning of THz waves through 2D electron gas (2DEG) incorporated with a hybrid design of metasurface has attracted keen interest due to the combined merits of deliberate structural design, rapid switching speed and the process compatibility. Current meta‐modulator enables very high modulation depth but encounter limited bandwidth. In this paper, by taking into account the co‐functional effects of temperature and voltage‐dependent dynamic control on transmission amplitude, a 2DEG‐based GaN‐on‐Si modulator with two switchable operational states (or four modes) of active wave control is proposed. Under cryogenic temperature conditions, the proposed device exhibits prominent 2D plasmons characteristics with switchable transitions between the gated mode and ungated mode for active control. Under room temperature conditions, the proposed device exhibits non‐resonance broadband spectra characteristics with tunable transitions between the linearity mode and depletion mode for transmission control. The scheme provides an option for the development of the actively tunable THz meta‐modulator and paves a way for the robust multifunctionality of electrically controllable THz switching, and biosensors.

Study of soft X-ray radiation of plasma produced by interaction of laser radiation with copper targets at the “Kanal-2” facility

As part of the work on creating an x-ray microscope, experimental and theoretical studies of laser plasma of solid copper targets in the soft x-ray range were carried out. With a laser pulse duration of 2.5 ns (FWHM), the power density of the Nd:glass laser on the target is varied in the range 0.8 × 1013–4.2 × 1013 W/cm2. Experimental results demonstrated the presence of intense plasma emission in spectral ranges of water and carbon windows, and the number of photons of the most intense lines was calculated. Spatio-temporal studies of copper plasma have demonstrated intense emission in the wavelength range shorter than 15 Å, and the images of plasma emission in time-integrated and linear sweep modes are shown. The simulations of the interaction of the specified laser radiation flux with copper targets were carried out taking into account the transfer of self-radiation in plasma. The non-local thermodynamic equilibrium optical properties of the plasma were used. As a result of calculations, profiles of density, temperature, electron thermal conductivity flux, emissivity of plasma, and self-radiation flux were obtained. The calculated spectrum of the outgoing radiation is consistent with that obtained at the experiment.

An attention-based channel estimation network with residual mechanism for 5G OFDM systems

Abstract Due to the significant increase in data transmission speed and gradual increase in Doppler frequency shift, channel estimation accuracy has become one of the most prioritized considerations in many cases. Specifically, we propose an attention-based channel estimation network with a residual mechanism, named TRCE-Net. In our design, the use of the multi-head attention mechanism at the input of the encoder is to obtain richer feature details. A linear series decoder module is implemented by leveraging multiple residual networks with skip connections. This novel design is capable of improving the channel estimation accuracy after deepening the network while effectively preventing degradation. To lessen the number of parameters that the network needs to learn, we introduce the bi-linear interpolation mechanism to replace the traditional up-sampling layer to mitigate both computational overhead and model complexity. According to the simulation results, our proposed TRCE-Net is superior to other state-of-the-art methods with regard to estimation accuracy and robustness to different maximum Doppler shifts, such as ResNet and InterpolateNet.

Multi-fidelity simulation of inlet mode transition with smooth thrust of turbine based combined cycle

A multi-fidelity simulation method of external and internal flow has been developed using commercial software to achieve a smooth thrust of the turbine-based combined-cycle (TBCC) propulsion system. This platform enables the investigation of the flow field and performance of the TBCC propulsion system at different mode transition schemes. The integrated multi-fidelity simulation includes the inlet, turbojet engine, ramjet engine, and nozzle, providing insights into the operation process of the TBCC propulsion system during the transition from turbojet mode to ramjet mode. Three mode transition schemes are proposed: critical mode transition, constant aerodynamic interface plane (AIP) Mach number mode transition, and linear mode transition. From the perspective of TBCC inlet, the performance of the critical mode transition exhibits the best performance among these mode transition schemes, while the linear mode transition performs the worst. However, from the viewpoint of the TBCC propulsion system and the hypersonic vehicle, the performance of constant AIP Mach number mode transition is the best. The non-dimensional thrust increases almost linear from 1.0 to 1.2, enabling hypersonic vehicle to accelerate steadily during the transition from turbojet mode to ramjet mode.

Multimode solitons in optical fibers: a review

This review describes recent theoretical and experimental advances in the area of multimode solitons, focusing primarily on multimode fibers. We begin by introducing the basic concepts such as the spatial modes supported by a multimode fiber and the coupled mode equations for describing the different group delays and nonlinear properties of these modes. We review several analytic approaches used to understand the formation of multimode solitons, including those based on the 3D+1 spatiotemporal nonlinear Schrödinger equation (NLSE) and its approximate 1D+1 representation that has been found to be highly efficient for studying the self-imaging phenomena in graded-index multimode fibers. An innovative Gaussian quadrature approach is used for faster numerical simulations of the 3D+1 NLSE. The impact of linear mode coupling is discussed in a separate section using a generalized Jones formalism because of its relevance to space-division multiplexed optical communication systems. The last section is devoted to the relevant experimental studies involving multimode solitons.

Static analysis of wind blades based on weight loads to the gravitation and the centrifugal forces Using Finite Element

Static analysis of wind turbine blades that convert kinetic energy using wind to electrical power has been analyzed using Ansys model. The geometry was imported in ANSYS workbench 2020R1, where the material was changed to Epoxy E-Glass Wet. The mesh independence that occurred at 800 and 600 element sizes and an element size of 800 was chosen for subsequent static analysis. The static analysis shows that the total deformation and von Mises stress of the wind turbine blade was improved at both the vertical position and the horizontal position by 40.0% and 38.61%, respectively. Besides, the static analysis showed an almost linear mode shape increased from mode lines. Nevertheless, Campbell's diagram showed that resonance vibration occurred at an amplitude of 5.5x106Pa with a corresponding frequency of 5Hz, which gave a rotational speed of 262.4x106 rpm. This shows that the impulse force is better applied in wind turbine blade transient analysis at a lower von Mises stress to attain a quicker damping response steady-state, which favors wind turbine blade analysis. Overall, the wind turbine blade is better designed at a vertical position to allow better deformation stress at a static position. Conversely, the von Mises stress showed 44.64% and 38.61% at horizontal and vertical positions. This also agrees with static total deformation, since stress is better managed at a lower percentage range.

Controllable Anime Image Editing via Probability of Attribute Tags

AbstractEditing anime images via probabilities of attribute tags allows controlling the degree of the manipulation in an intuitive and convenient manner. Existing methods fall short in the progressive modification and preservation of unintended regions in the input image. We propose a controllable anime image editing framework based on adjusting the tag probabilities, in which a probability encoding network (PEN) is developed to encode the probabilities into features that capture continuous characteristic of the probabilities. Thus, the encoded features are able to direct the generative process of a pre‐trained diffusion model and facilitate the linear manipulation. We also introduce a local editing module that automatically identifies the intended regions and constrains the edits to be applied to those regions only, which preserves the others unchanged. Comprehensive comparisons with existing methods indicate the effectiveness of our framework in both one‐shot and linear editing modes. Results in additional applications further demonstrate the generalization ability of our approach.

Light field images super-resolution method based on hybrid low-dimensional spatial–angular interaction feature and linear complementation epipolar feature

Light-field (LF) cameras record 4D information about the intensity and angle of light, but limited by the resolution of the sensor, LF images require a trade-off between spatial and angular resolution, which results in generally low spatial resolution for LF images. We work on spatial super-resolution reconstruction (SR) of LF images, but due to the high dimensionality of 4D LF, it is difficult to process it directly, so we decompose 4D LF into low-dimensional sub-spaces. Since the 4D features of interest to different low-dimensional sub-spaces are different, we design a hybrid network structure—HSAESR, which processes multiple low-dimensional sub-spaces individually to adequately model the texture information in the 4D LF. HSAESR is designed to reconstruct Macro Pixel Images (MacPI) and Extremely Planar Images (EPI) respectively, and the final reconstruction results are weighted and fused. For MacPI, a CNN-based feature interaction module is designed using a novel asymptotic ’grid’ interaction approach to fully utilize the correlation between the 2D spatial dimension and the 2D angular dimension sub-spaces in 4D LF. For EPI, a Transformer-based epipolar feature linear complementation module is designed learning global and non-global multi-directional epipolar feature correlations, which learns feature linear correlation factor (α) and linear bias weight (β) through the correlation of non-global epipolar features, and corrects and complements the global epipolar correlation features through feature linear complementation. Extensive experiments are conducted on five datasets, the results show that HSAESR further improves the performance of LF images spatial SR, the reconstruction results are better than the comparison methods.